Chase the Clock
Explore specialized visualizations to uncover trends, seasonality, and evolving patterns in time series data.
In our journey so far, we’ve learned to build insightful charts for various data distributions and to see multiple layers in our data. Now, we arrive at a very special kind of data that has its own unique rhythm and challenges: time series data. Imagine data that flows like a river, constantly changing and carrying clues about the past, present, and future. In this lesson, we will dive into what time series data is and explore powerful visualization techniques specifically designed to help us uncover its patterns, trends, and seasonal cycles.
The earliest known time series plot, created by William Playfair in 1786, shows England’s trade balance over time, a foundational step in modern data visualization.
What is time series visualization?
In theory, most of the data we’ve discussed so far could be shuffled around without losing its meaning. For example, if we have a list of customer ages, the order of those ages doesn’t usually matter. But with time series data, the order is everything!
Time series data is a collection of observations recorded over a specific time period. Each data point comes with a timestamp, which tells us exactly when it occurred. This sequence allows us to see how values change and evolve over moments, hours, days, months, or years.
Fun fact: Time series data is used by NASA to track everything from climate change to space shuttle performance.
Let’s think about common examples we encounter daily:
We often see this happen with stock prices, where the price of a company’s stock is recorded every minute, showing its precise evolution over time.
Another example is daily temperatures, which track how hot or cold it was at noon each day, revealing patterns of weather change.
Similarly, website traffic records the number of visitors to a website every hour, allowing us to see peak times and usage trends.
Even heart rate data, our pulse recorded every second by a fitness tracker, forms a time series, indicating changes in our physical state over time.
Time series visualization is simply the act of creating visual representations of this time-stamped data. It’s crucial because it allows us to quickly spot trends, detect unusual spikes or drops, identify repeating seasonal patterns, and understand how the data’s past influences its future. Without visualization, trying to find these insights in raw time series numbers would be like searching for a needle in a haystack. ...